Investigation Of Neural Mechanisms Underlying The Effect Of Working Memory Capacity On Distractor Suppression Using MRI Technology

Working memory capacity(WMC)reflects the ability to filter irrelevant from a large number of inputs.Previous behavioral and electrophysiological studies have shown that individuals with high WMC are able to suppress salient-but-irrelevant distractors better than those with low WMC,but neural substrates underlying such a cognitive difference remain largely unknown.Therefore,this study aims to explore neural mechanisms of distractor suppression with differential WMC using magnetic resonance imaging(MRI)technology.The present study recruited 88 young-healthy adults.Each subject performed a visual search task and a visual working memory task to measure their ability to suppress a salient-but-irrelevant distractor and WMC,respectively.Besides,each subject underwent structural MRI(s MRI)and resting-state functional MRI(f MRI)scans.Subsequently,the subjects were divided into the High-WMC and Low-WMC groups using the median value of their WMC.Behavioral results showed that the presence of a salient distractor significantly fastened subjects’ reaction time and improved accuracy,which was generally defined as “singleton benefit”.Furthermore,such a singleton benefit was considerably larger in the High-WMC group than the Low-WMC group,indicating a better distractor suppression ability for High-WMC individuals.Here,s MRI and rs-f MRI data were used to explore neural mechanisms underlying the effect of WMC on distractor suppression in terms of gray matter morphologies,resting-state functional connectivity,and resting-state functional connectome.1.Based on s MRI data,voxel-and deformation-based morphometry analyses were conducted to identify brain regions whose gray matter morphologies were correlated with individuals’ distractor suppression ability.We found that brain regions whose gray matter morphologies have significant but different associations of distractor suppression ability between the High-and Low-WMC groups were mainly within the frontoparietal network and default mode networks involving goal-driven and self-processing processes.On the other hand,brain regions whose gray matter morphologies have significant and similar associations of distractor suppression ability between the two groups were mainly within the ventral attention network.2.Based on brain regions whose gray matter morphologies were related to distractor suppression ability,voxel-wise functional connectivity analysis was calculated to explore whether intrinsic neural activities were correlated with distractor suppression ability as well.We identified significant correlations between distractor suppression ability within the High-WMC and the degree centrality of core regions of the frontoparietal network,default mode network,and ventral attention networks.In contrast,for the Low-WMC,there were significant correlations between distractor suppression ability and the regional homogeneity and fractional amplitude of low-frequency fluctuations of the core region of the ventral attention network.3.Integrating the whole-brain resting-state functional connectome and connectomebased predictive modeling approach,we found that cortico-cortical connections centered on the salience-limbic,motor,and visual association networks mainly contributed to the prediction of distractor suppression ability for the High-WMC group.In contrast,corticosubcortical connections centered on the subcortical and motor networks contributed to the Low-WMC group.Thus,the High-and Low-WMC groups were rooted in distinct functional architectures associated with distractor suppression.In summary,the present study explored neural mechanisms of distractor suppression in High-and Low-WMC individuals using s MRI and resting-state f MRI data.Our results demonstrated distinct brain structural and functional substrates associated with distractor suppression in individuals with different WMC.